Automated external defibrillators (AEDs) are used to analyze electrocardiographic (ECG) signals to detect ventricular fibrillation in victims who may be suffering cardiac arrest. The algorithm used within the AED must determine whether to deliver life-saving defibrillation therapy to the victim, and as such, needs to operate with minimal failure. Most AEDs are rate-based in that they compare a patient's monitored cardiac rhythm to preprogrammed nominal values. The problem with rate-based systems, however, is that often artifacts due to motion and/or cardiopulmonary resuscitation (CPR) can occur in the ECG signals potentially causing the AED to operate inappropriately, e.g., delivering a defibrillation pulse where none is needed or not delivering, a defibrillation pulse where one is needed.
As such, there is a need for a ventricular fibrillation detector that incorporates artifact extraction that can be implemented within an AED to reduce the potential for inappropriate operation. The ventricular fibrillation detector preferably operates continuously and is not rate based.